An HR guide to AI in 2020


Fifty per cent of workers are already using AI, and it is helping HR with everything from talent acquisition to learning and development, according to a new report. 

It is easy to believe that our efficiency and productivity naturally improves as time progresses. This bias probably comes from a truth about our own capabilities. As we learn and practise more, we become better at what we do. But in reality, despite our individual improvement, efficiency and productivity often regress.

Take recruitment, for example. In Australia the average amount of time it took to recruit a new employee went from 26 days in 2010 to 68 days in 2015. For more recent data, a new paper by Oracle says that, in the US, “despite new recruiting technologies, time to hire has actually increased in the last decade across most white-collar roles”.

Individual improvement, it seems, is no match for long decision-making processes, time spent waiting for approval and delayed initial candidate screenings. Or for the fact that most hiring is reactive, not proactive. Organisations tend to hire when there is a sudden gap instead of strategically filling the roles of the future.

It’s not surprising then that the same report states that in 2019 use of artificial intelligence (AI) by workers grew to 50 per cent, up from 32 per cent in 2018. The connection is a direct one. Although a lot of people have become jaded to the promise of AI, it underpins a lot of the software advances of the past five years. The problem for HR is often not knowing what’s actually available out there that can help them do their jobs more effectively.

Oracle’s paper, AI In Human Resources: The Time Is Now, delves into this. It explains how several HR functions are currently improving their productivity with AI.

Returning to recruitment, the report breaks down the value AI is adding to this crucial organisational need into four parts: sourcing, screening and interviewing, selecting and offering, and onboarding. Let’s look at some of the more impressive AI capabilities in two of these.

1. Candidate screening

The all-important initial screening of candidates is typically a massive time drain for HR. Trying to maintain your attention while reading through very similar resumes is no easy task. But it’s the kind of routine function that machine learning algorithms excel at. The evidence shows they do it better (maybe partially because they are incapable of getting tired or bored).

As the report says, AI can uncover top candidates by “finding the best match between job requirements and their skills and experience. Beyond a simple search for key terms, machine learning algorithms learn synonymous words that are commonly used in resumes.”

This means you don’t have to do a grueling search for the different way people describe their talents and past experiences (particularly a problem for job titles, which often vary from organisation to organisation).

2. Making the right offer

The worst moment to lose a candidate is right at the end of the process, when you have picked the one you’re sure will be right for your organisation. This often happens because it’s difficult to assess what they will accept because it is difficult to ascertain both market expectations and their expectations relative to the market.

The right AI solution can help with this. It can evaluate the local market, the listed salaries of competitor companies and give you a sense of what salary band you should be offering.

And, if you have access to it, AI can get quite granular and, as the report says, “increase recruiting efficacy by matching a specific offer with individual job and employee histories to calculate the odds of whether a candidate will accept”. 


To find out how AI is helping your speciality, whether that’s performance management, succession planning or career development, download Oracle’s report AI in Human Resources now.


I’ve heard this before…

It’s all easy to list the capabilities of AI and make it seem unimpeachably good. The reality is that most HR professionals are well aware that AI is not a cure-all. Indeed, it can bring its own problems. When they think of the capabilities of AI, they typically have three issues with it. 

  1. They worry about its robustness. How does it arrive at its conclusions? Is it actually working? And how can we be sure it isn’t just hardwiring our biases? A bad AI recruitment system is the bane of a diversity and inclusion agenda.
  2. They worry that it might not integrate with their current suite of tools
  3. They worry about the change management involved in teaching teams about the AI, and getting them to use it.

But modern AI developers are more than aware of these criticisms and are doing what they can to rectify them. The report addresses each of these concerns in turn. But the better proof that developers are overcoming these problems is research has found that 65 per cent of workers are optimistic, excited, and grateful about having robot ‘co-workers’. 

To find out how AI can help your speciality, whether that’s performance management, succession planning or career development, download Oracle’s report AI in Human Resources.

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An HR guide to AI in 2020


Fifty per cent of workers are already using AI, and it is helping HR with everything from talent acquisition to learning and development, according to a new report. 

It is easy to believe that our efficiency and productivity naturally improves as time progresses. This bias probably comes from a truth about our own capabilities. As we learn and practise more, we become better at what we do. But in reality, despite our individual improvement, efficiency and productivity often regress.

Take recruitment, for example. In Australia the average amount of time it took to recruit a new employee went from 26 days in 2010 to 68 days in 2015. For more recent data, a new paper by Oracle says that, in the US, “despite new recruiting technologies, time to hire has actually increased in the last decade across most white-collar roles”.

Individual improvement, it seems, is no match for long decision-making processes, time spent waiting for approval and delayed initial candidate screenings. Or for the fact that most hiring is reactive, not proactive. Organisations tend to hire when there is a sudden gap instead of strategically filling the roles of the future.

It’s not surprising then that the same report states that in 2019 use of artificial intelligence (AI) by workers grew to 50 per cent, up from 32 per cent in 2018. The connection is a direct one. Although a lot of people have become jaded to the promise of AI, it underpins a lot of the software advances of the past five years. The problem for HR is often not knowing what’s actually available out there that can help them do their jobs more effectively.

Oracle’s paper, AI In Human Resources: The Time Is Now, delves into this. It explains how several HR functions are currently improving their productivity with AI.

Returning to recruitment, the report breaks down the value AI is adding to this crucial organisational need into four parts: sourcing, screening and interviewing, selecting and offering, and onboarding. Let’s look at some of the more impressive AI capabilities in two of these.

1. Candidate screening

The all-important initial screening of candidates is typically a massive time drain for HR. Trying to maintain your attention while reading through very similar resumes is no easy task. But it’s the kind of routine function that machine learning algorithms excel at. The evidence shows they do it better (maybe partially because they are incapable of getting tired or bored).

As the report says, AI can uncover top candidates by “finding the best match between job requirements and their skills and experience. Beyond a simple search for key terms, machine learning algorithms learn synonymous words that are commonly used in resumes.”

This means you don’t have to do a grueling search for the different way people describe their talents and past experiences (particularly a problem for job titles, which often vary from organisation to organisation).

2. Making the right offer

The worst moment to lose a candidate is right at the end of the process, when you have picked the one you’re sure will be right for your organisation. This often happens because it’s difficult to assess what they will accept because it is difficult to ascertain both market expectations and their expectations relative to the market.

The right AI solution can help with this. It can evaluate the local market, the listed salaries of competitor companies and give you a sense of what salary band you should be offering.

And, if you have access to it, AI can get quite granular and, as the report says, “increase recruiting efficacy by matching a specific offer with individual job and employee histories to calculate the odds of whether a candidate will accept”. 


To find out how AI is helping your speciality, whether that’s performance management, succession planning or career development, download Oracle’s report AI in Human Resources now.


I’ve heard this before…

It’s all easy to list the capabilities of AI and make it seem unimpeachably good. The reality is that most HR professionals are well aware that AI is not a cure-all. Indeed, it can bring its own problems. When they think of the capabilities of AI, they typically have three issues with it. 

  1. They worry about its robustness. How does it arrive at its conclusions? Is it actually working? And how can we be sure it isn’t just hardwiring our biases? A bad AI recruitment system is the bane of a diversity and inclusion agenda.
  2. They worry that it might not integrate with their current suite of tools
  3. They worry about the change management involved in teaching teams about the AI, and getting them to use it.

But modern AI developers are more than aware of these criticisms and are doing what they can to rectify them. The report addresses each of these concerns in turn. But the better proof that developers are overcoming these problems is research has found that 65 per cent of workers are optimistic, excited, and grateful about having robot ‘co-workers’. 

To find out how AI can help your speciality, whether that’s performance management, succession planning or career development, download Oracle’s report AI in Human Resources.

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